EURO 2024 Copenhagen
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2197. Bi-objective sustainable crowdshipping with multi types of occasional drivers

Invited abstract in session TA-24: Sustainability in Vehicle Routing, stream Sustainable Supply Chains.

Tuesday, 8:30-10:00
Room: 83 (building: 116)

Authors (first author is the speaker)

1. Muhammad Khakim Habibi
Supply Chain Management & Information Systems, ESC Rennes School of Business
2. Daniel Sanchez Pineda
Département Automatique, Productique et Informatique (DAPI), IMT Atlantique
3. Audrey Cerqueus
DAPI, IMT Atlantique
4. Alexandre Dolgui
LS2N, IMT Atlantique

Abstract

Being competitive in last-mile delivery is a key factor for retailers, considering both cost and customer satisfaction. Crowdshipping addresses this by using ordinary people making deliveries on their habitual routes, being presented as a sustainable option. Yet, industrial initiatives have shown that it does not imply to be sustainable as compensation can attract more people, executing deliveries out of their normal routes. Our work introduces a crowdshipping problem optimizing both cost and CO2 emissions in a deterministic approach, referred to as the Bi-Objective Vehicle Routing Problem with Multi types of Occasional Drivers and Time Windows (BO-VRPMODTW). It generalizes the participation of Occasional Drivers (ODs) using different types of vehicles (fueled and non-fueled). The compensation policy defined assigns higher compensation to the non-fueled type. An epsilon constraint approach and a Column Generation-based epsilon approach were developed by considering short instances of clustered and random clients. The first experiments exhibit a competitive CPU time obtained by the latter approach. Also, it solves small and medium instances with an optimality gap smaller than 5%. Managerial insights on the impact of OD usage cost and CO2 are provided.

Keywords

Status: accepted

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